Many different error detection and compensation processes have been developed to read damaged barcodes or, generally speaking, encoded messages. For example, Reed Solomon Error Correction can be used with several different technologies including reading of damaged barcodes, as well as QR-Codes or other decode implementations such as, for example, consumer electronics, data transmission technologies and computer applications, amongst others.
By way of an illustrative example, barcodes can be scanned by optical scanners called barcode readers. These optical scanners can be a handheld device, e.g., portable digital assistants, stationary devices or other computing devices. In any scenario, the barcode reader is designed to read and decode the barcode. However, decoding of barcodes is a complicated process, particularly when the barcode is damaged or obscured in some manner. For example, the barcode reader can have difficulty decoding the barcode due to it being partially obscured within a window of an envelope, cut off or damaged, amongst a host of other conceivable issues.
In an attempt to compensate for such issues, many different error detection and compensation processes have been developed. Illustratively, a widely used process is the Reed-Solomon approach. The Reed-Solomon approach is a systematic way of building codes that could detect and correct multiple random symbol errors. Although this is a very effective approach, codes that are based on Reed Solomon Error Correction are susceptible to False Positives when decoding is too aggressive at using the correction capacity or False Negatives when decoding is too conservative. To compensate for such, existing solutions use a single threshold to control both of these situations, which is optimal for neither.